| Literature DB >> 30078923 |
Jean-Paul Chavas1, Corbett Grainger1, Nicholas Hudson1.
Abstract
Economists modeling climate policy face an array of choices when modeling climate change, including the role of uncertainty/ambiguity, irreversibility, and tipping points. After filtering out estimated cycles due to orbital climate forcing, we use a threshold quantile autoregressive model to characterize anomalies in atmospheric CO2 concentrations. We then test for local instability and tipping points, and we characterize the stationary distribution of anomalies. We find evidence of nonlinear dynamics, tipping points and a non-normal stationary distribution.Entities:
Keywords: Climate change; Nonlinear dynamics; Threshold quantile autoregression; Tipping points
Year: 2016 PMID: 30078923 PMCID: PMC6071419 DOI: 10.1016/j.jebo.2016.01.013
Source DB: PubMed Journal: J Econ Behav Organ ISSN: 0167-2681